Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI.

BACKGROUND: Axillary lymph node status is important for breast cancer staging and treatment planning as the majority of breast cancer metastasis spreads through the axillary lymph nodes. There is currently no reliable noninvasive imaging method to detect nodal metastasis associated with breast cancer. MATERIALS AND METHODS: Magnetic resonance imaging (MRI) data were those from the peak contrast dynamic image from 1.5 Tesla MRI scanners at the pre-neoadjuvant chemotherapy stage. Data consisted of 66 abnormal nodes from 38 patients and 193 normal nodes from 61 patients. Abnormal nodes were those determined by expert radiologist based on 18Fluorodeoxyglucose positron emission tomography images. Normal nodes were those with negative diagnosis of breast cancer. The convolutional neural network consisted of 5 convolutional layers with filters from 16 to 128. Receiver operating characteristic analysis was performed to evaluate prediction performance. For comparison, an expert radiologist also scored the same nodes as normal or abnormal. RESULTS: The convolutional neural network model yielded a specificity of 79.3% ± 5.1%, sensitivity of 92.1% ± 2.9%, positive predictive value of 76.9% ± 4.0%, negative predictive value of 93.3% ± 1.9%, accuracy of 84.8% ± 2.4%, and receiver operating characteristic area under the curve of 0.91 ± 0.02 for the validation data set. These results compared favorably with scoring by radiologists (accuracy of 78%). CONCLUSION: The results are encouraging and suggest that this approach may prove useful for classifying lymph node status on MRI in clinical settings in patients with breast cancer, although additional studies are needed before routine clinical use can be realized. This approach has the potential to ultimately be a noninvasive alternative to lymph node biopsy.

Peripheral nerve field stimulation in chronic abdominal pain.

INTRODUCTION: Spinal Cord Stimulation (SCS) has become an accepted therapeutic modality for the treatment of intractable pain syndromes, primarily used today in the settings of failed back surgery syndrome, neuropathic back and limb pain. The use of spinal cord stimulators for peripheral nerve field electrostimulation is becoming increasingly recognized as a safe, effective alternative for chronic pain conditions that are refractory to medical management and do not respond to traditional dorsal column stimulation. Advances in technology have allowed for minimally invasive percutaneous placement of multipolar leads with complex programmable systems to provide patient- controlled relief of pain in precisely targeted regions. With these improvements in hardware, the use of Peripheral Nerve Field Stimulation (PNFS) appears to have an untapped potential for providing patients with pain relief for a wider range of underlying conditions than was previously believed possible. We present three cases, each with a different etiology of chronic abdominal pain: one with inguinal neuralgia, one with chronic pancreatitis, and one with pain following liver transplant. Each patient was refractory to conventional medical approaches. For all three patients, PNFS provided significant relief from pain, enabling patients to decrease or discontinue their opioid medications and to enjoy significant improvement in their quality of life. We conclude that PNFS is a safe, effective and minimally invasive treatment that may be used successfully for a wide variety of indications including chronic abdominal pain.